unsubscribeCancel a subscription by id. Ownership is enforced — you can only cancel your own subscriptions. The row is deactivated (not deleted) so its historical events stay available via recent_alerts.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Subscription id (uuid) returned by subscribe. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Adds important behavioral detail beyond annotations: 'The row is deactivated (not deleted) so its historical events stay available via recent_alerts.' Also clarifies ownership enforcement. Annotations already indicate non-destructive and idempotent, so description complements well.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three succinct sentences covering purpose, constraint, and side effect. No unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given tool simplicity (1 param, no output schema), description covers behavior, ownership, and side effects. Sufficient for agent understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and description adds meaning by specifying that id is 'returned by subscribe', linking to the subscription creation tool.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('cancel') and resource ('subscription by id'). It effectively distinguishes from the sibling 'subscribe' tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit ownership constraint ('you can only cancel your own subscriptions'), giving clear usage context. Does not explicitly mention alternatives but the sibling tool list includes 'subscribe' as counterpart.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Several tools are near-duplicates or overlapping entry points: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, discover_tools, and suggest_questions all serve overlapping query/discovery purposes. The polymarket tools and HubSpot tools are more distinct, but the set as a whole has fuzzy boundaries between many members.
Naming is inconsistent across the set: HubSpot tools use an hs_ prefix, Pipeworx tools mostly use bare verbs (ask_pipeworx, recall, forget), and other tools mix styles (ai_visibility_check, generate_llms_txt, polymarket_edges). The hs_* subset is consistent, but overall there is no single predictable pattern.
38 tools is too many for the apparent scope, especially since the server is named 'Hubspot' but only 6 of the tools are HubSpot-specific. A large portion of the catalog covers unrelated Pipeworx data access, prediction markets, memory, and npm scanning, making the set feel bloated and unfocused.
The HubSpot portion of the tool set is read-only: it can get, list, and search companies/contacts/deals, but has no create, update, or delete operations, leaving obvious lifecycle gaps. If the intended domain is actually Pipeworx/data research, the HubSpot tools seem like an unrelated afterthought, so the surface is incomplete for either interpretation.